{"id":"W4408204264","doi":"10.1093/rsq/hdae024","title":"The Invisibilised Labour of Diasporas as Co-sponsors in Refugee Sponsorship: Lessons <i>From</i> Canada","year":2025,"lang":"en","type":"article","venue":"Refugee Survey Quarterly","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council","keywords":"Refugee; Political science; Business; Law","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01043388,0.0004922886,0.0005945414,0.00181466,0.03658122,0.01570066,0.002313429,0.001835395,0.004791034],"category_scores_gemma":[0.01112401,0.0004646861,0.0002558891,0.0025325,0.02874453,0.005647872,0.01295302,0.00481259,0.0002871819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04982968,"about_ca_system_score_gemma":0.1057164,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8885208,"about_ca_topic_score_gemma":0.9621337,"domain_scores_codex":[0.9917575,0.004416508,0.000137747,0.0003226901,0.000705411,0.002660143],"domain_scores_gemma":[0.9877345,0.004876854,0.0008348706,0.0005730751,0.001653247,0.004327389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003469184,0.0000377629,0.007879105,0.00007857858,0.00000568355,0.000740009,0.966453,0.00003854228,0.0001411562,0.01162047,0.00385622,0.009114806],"study_design_scores_gemma":[0.000002844468,0.000007709888,0.003330553,0.0001659648,0.000002766772,0.00006944348,0.9791533,0.00001990042,0.00003665488,0.0005232716,0.01667853,0.00000909272],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9030952,0.004882228,0.0005734586,0.038876,0.0003659611,0.0001230082,0.000149319,0.00001337682,0.05192143],"genre_scores_gemma":[0.9918358,0.002489852,0.0002615156,0.001224019,0.00003314306,0.00002967037,0.00003168893,0.00001321985,0.004081114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1114792,"threshold_uncertainty_score":0.3615413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02373175067237929,"score_gpt":0.3245130578591005,"score_spread":0.3007813071867211,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}